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Plan Review

Community
longranger2
plan-review

Use when the user says "/plan-review", "plan review", or "PRD review" and provides a plan file path that needs critical review and iterative refinement with Codex.

Overview

Publisherlongranger2
Repositoryclaude-gpt-workflow
Skill nameplan-review
Stars
81
Forks
12
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by longranger2 on GitHub. Read the source before you install it.

Installation

Install the Plan Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/longranger2/claude-gpt-workflow/tree/main/plan-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/longranger2/claude-gpt-workflow.git /tmp/claude-gpt-workflow
mkdir -p .claude/skills
cp -r /tmp/claude-gpt-workflow/plan-review .claude/skills/plan-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plan Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Plan Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Plan Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Plan Review Skill

Purpose

When the user runs /plan-review {plan-file-path}, start the "adversarial plan iteration" workflow:

  1. I (Claude Code) ask Codex to perform a critical review of the specified plan.
  2. I read the review produced by Codex and evaluate whether its suggestions are sound.
  3. I revise the plan based on valid suggestions and write changes back to the original plan file.
  4. If the review status is NEEDS_REVISION, I automatically ask Codex to review again.
  5. Repeat until consensus is reached as MOSTLY_GOOD or APPROVED.

Usage

/plan-review plans/my-feature-plan.md

Session Reuse

After each Codex invocation, extract session_id=xxx from the script output and save it as the session ID for the current task. In later Codex calls for the same task, pass --session <id> to reuse context so Codex remembers prior review history and can stay consistent across multiple rounds.

My Workflow (Claude Code)

Step 1: Determine the Review File

Derive the review file path from the plan file name:

  • plans/auth-refactor.md → reviews/auth-refactor-review.md
  • Rule: reviews/{plan-file-name-without-.md}-review.md

If the review file already exists, this is not the first round, so Codex must track the resolution status of issues from the previous round.

Step 2: Ask Codex to Review the Plan

Use the /codex skill and give Codex the following instruction:

Read the contents of {plan-file-path} and review it critically as an independent third-party reviewer.

Requirements:
- Raise at least 10 concrete and actionable improvement points
- Each issue must include: issue description + exact location/reference in the plan + improvement suggestion
- Use severity levels: Critical > High > Medium > Low > Suggestion
- If {review-file-path} already exists, read it first and track the resolution status of previous issues in the new round

Analysis dimensions, choosing the relevant ones based on the plan type:
- Architectural soundness: overdesign vs underdesign, module boundaries, single responsibility
- Technology choices: rationale, alternatives, compatibility with the existing project stack
- Completeness: missing scenarios, overlooked edge cases, dependency and impact scope
- Feasibility: implementation complexity, performance risks, migration and compatibility concerns
- Engineering quality: whether it follows the Code Quality Hard Limits in `CLAUDE.md`
- User experience: interaction flow, error/loading states, i18n when relevant
- Security: authentication, authorization, data validation when relevant

Append the current review round to {review-file-path}, creating the file if it does not exist.
Separate rounds with `---` and append new rounds at the end of the file. Use this format:

---

## Round {N} — {YYYY-MM-DD}

### Overall Assessment
{2-3 sentence overall assessment}
**Rating**: {X}/10

### Previous Round Tracking (R2+ only)
| # | Issue | Status | Notes |
|---|-------|--------|-------|

### Issues
#### Issue 1 ({severity}): {title}
**Location**: {location in the plan}
{issue description}
**Suggestion**: {improvement suggestion}
... (at least 10 issues)

### Positive Aspects
- ...

### Summary
{Top 3 key issues}
**Consensus Status**: NEEDS_REVISION / MOSTLY_GOOD / APPROVED

Key principle: be a critical reviewer, not a yes-man. Every issue must be specific enough that someone knows how to revise the plan.

When the review file is created for the first time, add this header at the top:

markdown
# Plan Review: {plan title}

**Plan File**: {plan-file-path}
**Reviewer**: Codex

Step 3: Read the Review and Revise the Plan

After Codex finishes, I read the latest review round in the review file:

  1. Evaluate each issue raised by Codex one by one.
  2. Adopt valid suggestions and revise the plan file.
  3. If rejecting an unreasonable suggestion, optionally note the reason briefly in the plan.
  4. Update the original plan file directly instead of creating a new file.

Step 4: Decide Whether to Continue Iterating

Use the Consensus Status provided by Codex:

StatusMy Action
NEEDS_REVISIONRevise the plan, then automatically ask Codex to review again and return to Step 2
MOSTLY_GOODRevise the plan, then tell the user the plan is mostly mature and ask whether another review round is needed
APPROVEDTell the user the plan has passed review and is ready for implementation

Step 5: Wrap Up

After the iteration is complete, report the following to the user:

  • How many review rounds were completed
  • Which major areas were improved
  • The final plan file path
  • The review log file path

File Convention

  • One review file per plan: reviews/{topic}-review.md
  • {topic} is the plan file name without .md
  • Append all rounds to the same file and separate them with ---
  • Example: plans/auth-refactor.md -> reviews/auth-refactor-review.md

Frequently asked questions

What does the Plan Review AI skill do?

Use when the user says "/plan-review", "plan review", or "PRD review" and provides a plan file path that needs critical review and iterative refinement with Codex.

Why use Plan Review on TypingMind?

Because you install it once and use it with any model. Plan Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Plan Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/longranger2/claude-gpt-workflow/tree/main/plan-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Plan Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Plan Review?

As many as you like. As long as a model supports skills, you can use Plan Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Plan Review AI skill free?

Yes. It is published on GitHub by longranger2 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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